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LinkMCP: hosted LinkedIn MCP server

by io.linkmcp
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Comment on Post

linkedin_comment_on_post
Destructive

Comment on a LinkedIn post. Supports threaded replies (replying to an existing comment) and @mentions. Mention identifiers are automatically resolved - you can use profile URLs, slugs, or URNs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesComment text (max 1250 characters). Use \n for line breaks. Use {{0}}, {{1}} etc. to insert mentions from the mentions array.
as_pageNoOptional. Post the comment as a LinkedIn company page that you administer: the page_id from linkedin_list_company_pages. Omit it to comment as yourself.
post_idNoActivity URN (urn:li:activity:123) or numeric activity ID. Use post_url or post_id, at least one is required.
mentionsNoOptional mentions array. Reference in text as {{0}}, {{1}} etc. Each identifier is resolved via profile lookup.
post_urlNoLinkedIn post URL (e.g. https://www.linkedin.com/feed/update/urn:li:activity:123 or /posts/ style).
comment_idNoOptional. ID of an existing comment to reply to (threaded reply).
content_checkNoControls LLM content artifact detection (default: "strict"). "strict" rejects text containing Unicode dashes (— – −) and other LLM artifacts. "autofix" automatically replaces em dashes with standard dashes. "disabled" skips all content checks.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / as_page
      Added value: +{
+  "description": "Optional. Post the comment as a LinkedIn company page that you administer: the page_id from linkedin_list_company_pages. Omit it to comment as yourself.",
+  "type": "string"
+}
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=false, destructiveHint=true, openWorldHint=true and idempotentHint=false, so the agent knows this is a public, non-idempotent write. The description adds that mention identifiers are auto-resolved, which is useful context, but it never states that the comment is publicly visible, irreversible, or subject to platform rate limits — the exact risks an agent should weigh before a destructive public write.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the primary action, then capability scope, then the mention-resolution note. No filler, though the final sentence partially duplicates the schema's 'Automatically resolved' wording rather than earning new information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive, multi-parameter write with no output schema, the description covers what the tool does and its two special modes, but says nothing about the result (e.g. whether the created comment ID is returned) or the visibility/permanence of the effect. It is adequate but leaves the post-call expectations to inference.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so every parameter is already documented in the schema (including the {{0}} placeholder convention, identifier formats, comment_id for threading, and content_check semantics). The description largely restates what the schema says about URL/slug/URN resolution. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Comment on a LinkedIn post') and immediately scopes the capability with threaded replies and @mentions. An agent can distinguish this from linkedin_create_post, linkedin_react_to_post and linkedin_get_post_comments without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the verb — use this to post a comment — and the mention/reply sentences hint at the threaded variant, but there is no explicit 'use this instead of X' guidance or when-not condition. The description never names a sibling tool (e.g. linkedin_create_post for top-level posts, linkedin_react_to_post for reactions).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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